IEEE IGARSS 2022 || Kuala Lumpur, Malaysia || 17

TH6.V7: Classification and Clustering MMV III

Thu, 21 Jul, 21:35 - 22:45 Malaysia Time (UTC +8)
Thu, 21 Jul, 15:35 - 16:45 Central European Time (UTC +1)
Thu, 21 Jul, 13:35 - 14:45 UTC
Thu, 21 Jul, 09:35 - 10:45 Eastern Time (UTC -5)

Location: Virtual Room 7

Session Type: Multimedia Virtual

Session Co-Chairs: Qin Yan, China University of Geosciences (Wuhan) and Xiaofeng Yang, Aerospace Information Research Institute (AIRCAS)

Session Manager: Khe Kheng Kow

Track: Data Analysis Methods (Optical, Multispectral,Hyperspectral, SAR)

TH6.V7.1: BALANCED RANDOM FOREST MODEL IS MORE SUITABLE FOR WILDFIRE RISK ASSESSMENT

Zili Wang, Binbin He, Xiaoying Lai, University of Electronic Science and Technology of China, China

TH6.V7.2: SELF-SUPERVISED FEATURE LEARNING AND FEW-SHOT LAND COVER CLASSIFICATION FOR CROSS-MODAL REMOTE SENSING IMAGES

Zhixiang Xue, Xuchu Yu, Pengqiang Zhang, Xiong Tan, Anzhu Yu, Bing Liu, PLA Strategic Support Force Information Engineering University, China

TH6.V7.3: ANALYSIS OF MACHINE LEARNING TECHNIQUES FOR CARBONATE OUTCROP IMAGE CLASSIFICATION IN LANDSAT 8 SATELLITE DATA

Vinicius Sales, Graciela Racolte, Ademir Marques Jr., Daniel Zanotta, Luiz Gonzaga Jr., Mauricio Veronez, Vale do Rio dos Sinos University, Brazil; Caroline Cazarin, Cenpes Petrobras, Brazil

TH6.V7.4: EVALUATION OF FIRE PRODUCTS USING SPATIO-TEMPORAL CLUSTERING METHOD

Miao Jiao, Zhenyu Kang, Xingwen Quan, University of Electronic Science and Technology, China

TH6.V7.5: USING DRONES AND DEEP NEURAL NETWORKS TO DETECT HALYOMORPHA HALYS IN ECOLOGICAL ORCHARDS

Loretta Ichim, Radu Ciciu, Dan Popescu, University POLITEHNICA of Bucharest, Romania

TH6.V7.6: DEEP ENSEMBLE LEARNING FOR LAND COVER CLASSIFICATION BASED ON HYPERSPECTRAL PRISMA IMAGE

Bahareh Kalantar, Naonori Ueda, RIKEN Center for Advanced Intelligence Project, Japan; Seyd Teymoor Seydi, School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Iran; Vahideh Saeidi, Department of Mapping and Surveying, Darya Tarsim Consulting Engineers Co. Ltd.,, Japan; Alfian Abdul Halin, Department of Multimedia, Faculty of Computer Science & Information Technology, Universiti Putra Malaysia, Malaysia; Farzin Shabani, Flinders University, Australia

TH6.V7.1: BALANCED RANDOM FOREST MODEL IS MORE SUITABLE FOR WILDFIRE RISK ASSESSMENT

TH6.V7.2: SELF-SUPERVISED FEATURE LEARNING AND FEW-SHOT LAND COVER CLASSIFICATION FOR CROSS-MODAL REMOTE SENSING IMAGES

TH6.V7.3: ANALYSIS OF MACHINE LEARNING TECHNIQUES FOR CARBONATE OUTCROP IMAGE CLASSIFICATION IN LANDSAT 8 SATELLITE DATA

TH6.V7.4: EVALUATION OF FIRE PRODUCTS USING SPATIO-TEMPORAL CLUSTERING METHOD

TH6.V7.5: USING DRONES AND DEEP NEURAL NETWORKS TO DETECT HALYOMORPHA HALYS IN ECOLOGICAL ORCHARDS

TH6.V7.6: DEEP ENSEMBLE LEARNING FOR LAND COVER CLASSIFICATION BASED ON HYPERSPECTRAL PRISMA IMAGE

TH6.V7.7: SUPERPIXEL CORRECTION BASED LABEL PROPAGATION FOR HYPERSPECTRAL IMAGES CLASSIFICATION

TH6.V7.8: NQ-PROTONET: NOISY QUERY PROTOTYPICAL NETWORK FOR FEW-SHOT REMOTE SENSING SCENE CLASSIFICATION

TH6.V7.9: CLASSIFYING HYPERSPECTRAL IMAGES WITH CAPSULE NETWORK AND ACTIVE LEARNING

TH6.V7.10: A SPATIAL-CHANNEL ATTENTION-BASED CONVOLUTIONAL NEURAL NETWORK FOR REMOTE SENSING IMAGE CLASSIFICATION